Keyword Spotting
Overview
Keyword spotting identifies trigger words or user-specified phrases in continuous speech, enabling voice interfaces without sending every utterance to full speech recognition. Systems commonly use compact convolutional or recurrent models over log-mel or MFCC features, alongside newer streaming, spiking, prototype-matching, and event-based approaches. To handle personalized phrases, pronunciation variation, speakers, and noise, methods add phoneme or text prompts, speaker verification, noise conditioning, and sometimes visual speech cues; evaluations include Google Speech Commands, LibriPhrase, and continuous-noise settings. The central challenge is balancing flexible vocabulary and reliable detection against false alarms, latency, memory, and energy on edge devices, since benchmark accuracy alone can miss real-world streaming behavior.
Latest papers
24 papers2 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.